Multidisciplinary diagnosis for children with autism – Functional assessment of development

2017 ◽  
Vol LXXVIII (2) ◽  
pp. 104-115
Author(s):  
Magdalena Wójcik
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Assessment ◽  
Motor Development ◽  
Diagnostic Procedure ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Assessment Tools ◽  
Therapeutic Interventions ◽  
Diagnostic Process

At the beginning of the article, the author presents basic information on the diagnostic procedure for autism spectrum disorder - main diagnostic criteria currently in force (DSM-5, ICD-10), taking into account the changes occurring in this area, as compared to the DSM-IV criteria, which were applicable until recently. In the second part, she emphasizes how important early diagnostic observation of autistic symptoms is. She analyzes in detail the patterns of normal child development from infancy to early childhood, taking into consideration characteristics that are important from the point of view of the diagnosis of autism: behaviors, emotions, relationships, physical development and communication; she also points to red flags for autism and distinctive early symptoms of autism spectrum disorder at each milestone in the development of infants and toddlers. The author also points out the importance of observing motor development in the child's first year of life in the ASD diagnostic procedure and emphasizes the need to analyze sensory processing difficulties and disorders, which is essential to develop appropriate therapeutic interventions; at the same time, she lists available assessment tools that are, in a way, an introduction to an extended diagnostic process. The third part of the article presents a detailed structure of diagnostic and therapeutic measures, which need to be developed individually for each child by a team of specialists. It also analyzes the special educator's assessment skills and points out threats coming from an inappropriate, unquestioning use of tools to provide functional assessment for children with autism; it also points to such tools that can complement the diagnostic process.

Language regression is associated with faster early motor development in children with autism spectrum disorder

2019 ◽  
Vol 13 (1) ◽  
pp. 145-156
Author(s):  
Liora Manelis ◽  
Gal Meiri ◽  
Michal Ilan ◽  
Hagit Flusser ◽  
Analya Michaelovski ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Motor Development ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Language Regression

scholarly journals Motor Development in Children With Autism Spectrum Disorder

2021 ◽  
Vol 9 ◽  
Author(s):  
Ashikin Mohd Nordin ◽  
Juriza Ismail ◽  
Norazlin Kamal Nor
Keyword(s):  
Autism Spectrum Disorder ◽  
Motor Development ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Fine Motor ◽  
Typically Developing ◽  
Developmental Profile ◽  
Typically Developing Children ◽  
Motor Delay

Objective: This study was conducted to determine the gross and fine motor profiles of children with autism spectrum disorder compared to typically developing children. Additionally, we also assessed if the motor delay was more pronounced with increasing age.Method: This was a retrospective study involving children aged 12–60 months of age comparing motor development in children with autism spectrum disorder with typically developing children. Their developmental profile was assessed using Schedule of Growing Skills II. Descriptive statistics was used to analyse the developmental profile between the groups.Results: ASD children had significant gross motor (6.7%) and fine motor delay (38.5%) compared to typically developing children, who did not show any delay. The motor delay in ASD children was more prominent in older children.Conclusion: It is important to assess motor development in ASD children as there is significant motor delay in these children compared to typically developing children, and the delay becomes more prominent with age. Early detection of motor delay could allow provision of early intervention services to optimize developmental outcomes.

scholarly journals Leisure and Quality of Life among Parents of Children with Autism Spectrum Disorder – A Review Based Analysis

2021 ◽  
pp. 176-188
Author(s):  
Menezes Ida Sylvia ◽  
Laveena D’Mello
Keyword(s):  
Quality Of Life ◽  
Autism Spectrum Disorder ◽  
Children With Autism ◽  
Well Being ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Assessment Tools ◽  
Children With Asd ◽  
Quality Life

Purpose: Owing to the time-consuming job of caring for their child's family and friends, parents of children with autism spectrum disorder risk losing family relationships. The main aim was to identify and intervene in the quality of life of parents, the interventions offered to parents as primary caregivers of children with ASD. To explore parents' perspectives on beneficent for children with autism in connection with formative years, resources, and to confront the consequences of upraising a child with ASD. Design/Methodology/Approach: Systematic literature, resulting in the publication of 27 studies that focused on the living standards of parents of children with ASD. Systematic literature scrutiny was performed using the search words "autism spectrum disorder," ‘primary caregiver/ parents/ mother” and "Quality of life" in the electronic databases Research gate, Academia, Google Scholar, and PsycInfo. Findings/Result: QOL autism-specific assessment tools were limited and hence, most studies have employed a general measure tool to assess the influence of the diagnosed disorder on the physical and psychological well-being of parents/caregivers. Originality/Value: The sequel of this study advocate that to date, the appraisal of quality life in parents of children with ASD into clinical practice has been rationalized by the shortage of autism-specific scales. As generically do not catch all pertinent aspects of living with ASD raising the need for immediate measures. Implementing parental interventions in parallel with the child’s interventions may raise QOL. Paper Type: Systematic literature review.

scholarly journals Reaction to diagnosis and subsequent health in mothers of children with autism spectrum disorder

Autism ◽  
2018 ◽  
Vol 23 (6) ◽  
pp. 1442-1448 ◽  
Author(s):  
Phil Reed ◽  
Lisa A Osborne
Keyword(s):  
Autism Spectrum Disorder ◽  
Health Status ◽  
Children With Autism ◽  
Physical Symptoms ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Diagnostic Process ◽  
Negative Consequences ◽  
Parental Health ◽  
Reaction To Diagnosis

The current study assessed whether reactions to diagnosis are associated with health status for mothers of children with autism spectrum disorder at the time of diagnosis, and whether such diagnostic-reaction resolution status is associated with changes in health status over time. A total of 84 mothers of children newly diagnosed with autism spectrum disorder, with stable reactions to diagnosis over a year, participated. Their perceptions of their physical and psychological functioning, and quality of life, were taken at the time of diagnosis and 1 year later. The mothers were also given the Reaction to Diagnosis Interview. Mothers who had an unresolved reaction to diagnosis had a worse health status in terms of their perception of the physical symptoms at the time of the diagnosis, and showed worsening levels of health over the period of a year, relative to mothers who had a resolved diagnostic status. These relationships were independent of other potential predictors of ill health in this sample. The findings point to the potential of the diagnostic process to negatively impact parental health. Given that this can have negative consequences for child prognosis, as well as parental health, there is a need to develop better understanding of the impacts of diagnostic practices.

scholarly journals Motor skills of children with autism spectrum disorder

2019 ◽  
Vol 21 ◽  
Author(s):  
Gabriele Radünz Kruger ◽  
Jennifer Rodrigues Silveira ◽  
Alexandre Carriconde Marques
Keyword(s):  
Autism Spectrum Disorder ◽  
Motor Skills ◽  
Motor Development ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Wilcoxon Test ◽  
Personal Hygiene ◽  
Gross Motor Development ◽  
Life Habits

Abstract The objective of this study is to describe variables of life habits associated with motor skills of children with autism spectrum disorder aged 8-10 years living in the city of Pelotas / RS. A questionnaire about lifestyle was applied and the Test of Gross Motor Development-2 (TGMD-2) was applied to assess motor skills. Independent T-test, ANOVA and Wilcoxon test were used to compare means. The study consisted of 49 individuals (42 males). The results indicate that the higher the level of ASD, the better the motor skills. Children making use of medications have greater deficits in motor skills. Higher scores on motor skills are associated with greater participation in physical education classes. Motor skills are strongly associated with independence in activities of the daily living, food, personal hygiene, dressing and bathing. The importance of the creation of PA programs aiming at improving the motor skills of this population was highlighted.

scholarly journals Comparison of performance on verbal and nonverbal multiple-cue responding tasks in children with ASD

2017 ◽  
Author(s):  
Lisa Lokshina ◽  
Alexander Faisman ◽  
Jonah Elgart ◽  
Edward Khokhlovich ◽  
Yuriy Gankin ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Important Implication ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Therapeutic Interventions ◽  
Pivotal Response Treatment ◽  
Newly Diagnosed ◽  
Therapeutic Application ◽  
Children With Asd

In this manuscript, we present data from an ongoing study of a tablet-based therapeutic application designed for newly diagnosed children with autism spectrum disorder (ASD) and modeled on Pivotal Response Treatment (PRT), a technique known to be effective in educating children with ASD. We describe the creation of a variety of analogous tasks that were presented both verbally and nonverbally within the application. This work presents our hypothesis that children with ASD perform better when a command is presented nonverbally. This approach may have important implication for the most effective way of delivering early therapeutic interventions to children with ASD.

scholarly journals A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder

2020 ◽  
Vol 10 (12) ◽  
pp. 949
Author(s):  
Md. Mokhlesur Rahman ◽  
Opeyemi Lateef Usman ◽  
Ravie Chandren Muniyandi ◽  
Shahnorbanun Sahran ◽  
Suziyani Mohamed ◽  
...  
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorder ◽  
Feature Selection ◽  
Early Identification ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Assessment Tools ◽  
Learning Methods ◽  
Machine Learning Methods

Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning’s speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.

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